Bibliographic record
Abstract
Social capital is an umbrella term used to describe aspects of social networks, relations, trust, and power, as a function of either the individual or a geographical entity (e.g., a city neighborhood). Increased attention is being paid to the role that social capital can play in determining a variety of physical health outcomes, though less attention has been paid to its role in determining mental health outcomes. This relative inattention continues despite a long historical tradition in psychiatry of exploring the role that socio-environmental factors can play in the etiology and course of mental illness. In this review, we begin by tracing the historical development of the concept of social capital, describing and analyzing competing definitions. We then proceed to review the published studies that examine the relationship between social capital and mental health-looking first at studies that focus on depression and anxiety, and second at studies that focus on psychoses. After briefly exploring whether social capital can have a detrimental effect on mental health, we discuss how knowledge regarding social capital may aid the clinician and mental health services. We go on to make a number of suggestions relevant to methodological, theoretical, and empirical advancement. These suggestions include refining the definitions of social capital, paying attention to communities without propinquity, and constructing contextual indicators of social capital. We conclude by remarking that social capital may be a promising heuristic for studies in community psychiatry and may even help individual clinicians in designing treatment plans. Despite all this promise, however, there is a lack of strong evidence supporting the hypothesis that social capital protects mental health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".